eptember 9, 2013 8:06 AM
Subject: Re: [R] sparse PCA using nsprcomp package
Hi John
> 1). Assume now I can calculate these "adjusted" standard deviation from
> sparse PCA, should the percent variation explained by each sparse PC be
> calculated using the sum of all these "
Hi John
> 1). Assume now I can calculate these "adjusted" standard deviation from
> sparse PCA, should the percent variation explained by each sparse PC be
> calculated using the sum of all these "adjusted" variance (i.e. square of the
> "adjusted" standard deviation) as the denominator (then t
in,
John
From: Christian Sigg
Cc: r-help@r-project.org
Sent: Thursday, September 5, 2013 2:43 PM
Subject: Re: [R] sparse PCA using nsprcomp package
Hi John
I am currently traveling and have sporadic net access, I therefore can only
answer briefly. It's
Hi John
I am currently traveling and have sporadic net access, I therefore can only
answer briefly. It's also quite late, I hope what follows still makes sense...
> For regular PCA by prcomp(), we can easily calculate the percent of total
> variance explained by the first k PCs by using cumsum(
Hi all, I am using nsprcomp() from nsprcomp package to run sparse PCA. The
output is very much like regular PCA by prcomp() in that it provides "sdev" for
standard deviation of principle components (PC).
For regular PCA by prcomp(), we can easily calculate the percent of total
variance explai
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